{"doi":"10.1101/2020.11.14.382473","title":"DeepMosaic: Control-independent mosaic single nucleotide variant detection using deep convolutional neural networks","abstract":"Introductory paragraph Mosaic variants (MVs) reflect mutagenic processes during embryonic development 1 and environmental exposure 2 , accumulate with aging, and underlie diseases such as cancer and autism 3 . The detection of MVs has been computationally challenging due to sparse representation in non-clonally expanded tissues. While heuristic filters and tools trained on clonally expanded MVs with high allelic fractions are proposed, they show relatively lower sensitivity and more false discoveries 4–9 . Here we present DeepMosaic, combining an image-based visualization module for single nucleotide MVs, and a convolutional neural networks-based classification module for control-independent MV detection. DeepMosaic achieved higher accuracy compared with existing methods on biological and simulated sequencing data, with a 96.34% (158/164) experimental validation rate. Of 932 mosaic variants detected by DeepMosaic in 16 whole genome sequenced samples, 21.89-58.58% (204/932-546/932) MVs were overlooked by other methods. Thus, DeepMosaic represents a highly accurate MV classifier that can be implemented as an alternative or complement to existing methods.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2020,"id":123139,"datarank":0.24141568686511508,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.0,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9568,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":565779,"name":"Xin Xu","orcid":"0000-0003-3973-2236","position":1,"is_corresponding":false},{"id":322760,"name":"Martin W. Breuss","orcid":"0000-0003-2200-8604","position":2,"is_corresponding":false},{"id":2971,"name":"Danny Antaki","orcid":"0000-0003-0381-7801","position":3,"is_corresponding":false},{"id":566520,"name":"Laurel Ball","orcid":null,"position":4,"is_corresponding":false},{"id":565780,"name":"Changuk Chung","orcid":"0000-0003-3628-6090","position":5,"is_corresponding":false},{"id":322758,"name":"Chen Li","orcid":"0000-0002-1790-6664","position":6,"is_corresponding":false},{"id":342945,"name":"Renee D. George","orcid":"0000-0003-0733-9691","position":7,"is_corresponding":false},{"id":21497,"name":"Yifan Wang","orcid":"0000-0001-8056-9755","position":8,"is_corresponding":false},{"id":566521,"name":"Taejeoing Bae","orcid":null,"position":9,"is_corresponding":false},{"id":21363,"name":"Alexej Abyzov","orcid":"0000-0001-5405-6729","position":10,"is_corresponding":false},{"id":565781,"name":"Liping Wei","orcid":"0000-0002-1795-8755","position":11,"is_corresponding":false},{"id":3004,"name":"Jonathan Sebat","orcid":"0000-0002-9087-526X","position":12,"is_corresponding":false},{"id":566522,"name":"NIMH Brain Somatic Mosaicism Network","orcid":null,"position":13,"is_corresponding":false},{"id":286444,"name":"Joseph G. Gleeson","orcid":"0000-0002-0889-9220","position":14,"is_corresponding":false},{"id":322763,"name":"Xiaoxu Yang","orcid":"0000-0003-0219-0023","position":0,"is_corresponding":true}],"reference_count":33,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:14:59.547352Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}